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Hands-On Computer Vision with Julia

Hands-On Computer Vision with Julia

By : Dmitrijs Cudihins
4 (1)
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Hands-On Computer Vision with Julia

Hands-On Computer Vision with Julia

4 (1)
By: Dmitrijs Cudihins

Overview of this book

Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code. . This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease.
Table of Contents (11 chapters)
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9
Assessments

Object detection using MobileNet-SSD

We will be using MobileNet-SSD network to detect objects such as cats, dogs, and cars in a photo. A combination of MobileNet and SSD gives outstanding results in terms of accuracy and speed in object detection activities. At the end of the section, you will be able to generate images containing bounding box and name of the object:

We always start the same, by loading Julia packages and defining path to opencv.pc:

ENV["PKG_CONFIG_PATH"] = "/Users/dc/anaconda/envs/python35/lib/pkgconfig"

using OpenCV
using Images, ImageView
using Cxx

The moment Julia packages are defined, we proceed to writing C++ code. Remember that C++ code is encapsulated within special syntax, as follows:

cxx"""
<<C++ code goes here>>
"""

The first thing when starting to write code in C++ is to add all prerequisites...

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